System for collecting and analyzing equipment telematic data

ABSTRACT

A system for collecting and analyzing equipment telematic data typically includes a processor, a memory, and an analysis module stored in the memory. The analysis module is typically configured for: receiving telematic data from a piece of equipment; parsing the telematic data to identify (i) location information and (ii) usage information for one or more tools; analyzing the telematic data to determine whether a job site condition has been satisfied; in response to determining that the job site condition has been satisfied, identifying a first job site location based on the location information of the telematic data; determining that the first job site location is not within an existing job site; and updating a job site database to include the first job site location.

CROSS-REFERENCE TO PRIORITY APPLICATION

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 62/789,890 entitled “SYSTEM FOR COLLECTING ANDANALYZING EQUIPMENT TELEMATIC DATA” (filed Jan. 8, 2019), which ishereby incorporated by reference in its entirety.

BACKGROUND

In many fields, such as electrical line work, construction, mining, oilor gas drilling, farming, fishing, and the like, it may be desirable totrack the time equipment and personnel are performing work at a jobsite, as opposed to time spent performing other activities, such astraveling, collecting materials at a yard, and taking meal breaks.Accordingly, a need exists for an improved way of tracking the timeequipment and personnel are performing work at a job site.

SUMMARY

In one aspect, the present invention embraces a system for collectingand analyzing equipment telematic data to accomplish various tasks, suchas identifying job site locations. The system typically includes aprocessor, a memory, and a network communication device. The system alsotypically includes an analysis module stored in the memory andexecutable by the processor. In one embodiment, the analysis module isconfigured for: receiving, via the network communication interface,telematic data from a piece of equipment; parsing the telematic data toidentify (i) location information and (ii) usage information for one ormore tools associated with the equipment (e.g., (i) a tool that is anintegrated component of the equipment or (ii) a handheld tool);analyzing the telematic data to determine whether a job site conditionhas been satisfied; determining that the job site condition has beensatisfied; in response to determining that the job site condition hasbeen satisfied, identifying a first job site location based on thelocation information of the telematic data; retrieving locationinformation for existing job sites from a job site database; determiningwhether the first job site location is within one of the existing jobsites; and in response to determining that the first job site locationis not within one of the existing job sites, updating the job sitedatabase to include the first job site location.

In one particular embodiment, either alone or in combination with otherparticular embodiments, analyzing the telematic data to determinewhether a job site condition has been satisfied comprises (i)determining whether the one or more tools have been used or (ii) using amachine learning algorithm to determine whether the job site conditionhas been satisfied.

In another particular embodiment, either alone or in combination withother particular embodiments, the analysis module is configured for:receiving, via the network communication interface, image data from thepiece of equipment; and analyzing the image data; wherein determiningthat the job site condition has been satisfied is based at least in parton analyzing the image data.

In another particular embodiment, either alone or in combination withother particular embodiments, analyzing the image data comprisesidentifying one or more objects associated with the job site condition.

In another particular embodiment, either alone or in combination withother particular embodiments, one or more tools comprise (i) a tool thatis an integrated component of the equipment or (ii) a handheld tool.

In another particular embodiment, either alone or in combination withother particular embodiments, the telematic data comprises a pluralityof telematic datasets.

In another particular embodiment, either alone or in combination withother particular embodiments, the analysis module is configured fordetermining an activity and/or location associated with each of thetelematic datasets.

In another particular embodiment, either alone or in combination withother particular embodiments, the analysis module is configured fordetermining a total time the piece of equipment is associated with eachof a plurality of activities and/or locations.

In another particular embodiment, either alone or in combination withother particular embodiments, the analysis module is configured fordetermining a total time the piece of equipment spent at the first jobsite location during a defined time period.

In another particular embodiment, either alone or in combination withother particular embodiments, the system comprises the piece ofequipment, wherein the piece of equipment comprises one or more sensorsthat collect telematic data.

In another aspect, the present invention embraces a method forcollecting and analyzing equipment telematic data. The method typicallycomprises receiving, via one or more computer processors, telematic datafrom a piece of equipment; parsing, via one or more computer processors,the telematic data to identify (i) location information and (ii) usageinformation for one or more tools associated with the equipment;analyzing, via one or more computer processors, the telematic data todetermine whether a job site condition has been satisfied; determining,via one or more computer processors, that the job site condition hasbeen satisfied; in response to determining that the job site conditionhas been satisfied, identifying, via one or more computer processors, afirst job site location based on the location information of thetelematic data; retrieving, via one or more computer processors,location information for existing job sites from a job site database;determining, via one or more computer processors, whether the first jobsite location is within one of the existing job sites; and in responseto determining that the first job site location is not within one of theexisting job sites, updating, via one or more computer processors, thejob site database to include the first job site location.

In one particular embodiment, either alone or in combination with otherparticular embodiments, analyzing the telematic data to determinewhether a job site condition has been satisfied comprises (i)determining whether the one or more tools have been used or (ii) using amachine learning algorithm to determine whether the job site conditionhas been satisfied.

In another particular embodiment, either alone or in combination withother particular embodiments, the method comprises receiving, via thenetwork communication interface, image data from the piece of equipment;and analyzing the image data; wherein determining that the job sitecondition has been satisfied is based at least in part on analyzing theimage data.

In another particular embodiment, either alone or in combination withother particular embodiments, analyzing the image data comprisesidentifying one or more objects associated with the job site condition.

In another particular embodiment, either alone or in combination withother particular embodiments, the one or more tools comprise (i) a toolthat is an integrated component of the equipment or (ii) a handheldtool.

In another particular embodiment, either alone or in combination withother particular embodiments, the telematic data comprises a pluralityof telematic datasets.

In another particular embodiment, either alone or in combination withother particular embodiments, the method comprises determining anactivity and/or location associated with each of the telematic datasets.

In another particular embodiment, either alone or in combination withother particular embodiments, the method comprises determining a totaltime the piece of equipment is associated with each of a plurality ofactivities and/or locations.

In another particular embodiment, either alone or in combination withother particular embodiments, the method comprises determining a totaltime the piece of equipment spent at the first job site location duringa defined time period.

In another aspect, the present invention embraces a computer programproduct for collecting and analyzing equipment telematic data. Thecomputer program product typically comprises a non-transitorycomputer-readable medium comprising computer-readable instructions that,when executed by a computer processor, cause the computer processor toperform the steps of: receiving telematic data from a piece ofequipment; parsing the telematic data to identify (i) locationinformation and (ii) usage information for one or more tools associatedwith the equipment; analyzing the telematic data to determine whether ajob site condition has been satisfied; determining that the job sitecondition has been satisfied; in response to determining that the jobsite condition has been satisfied, identifying a first job site locationbased on the location information of the telematic data; retrievinglocation information for existing job sites from a job site database;determining whether the first job site location is within one of theexisting job sites; and in response to determining that the first jobsite location is not within one of the existing job sites, updating thejob site database to include the first job site location.

The features, functions, and advantages that have been discussed may beachieved independently in various embodiments of the present inventionor may be combined with yet other embodiments, further details of whichcan be seen with reference to the following description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Having thus described embodiments of the invention in general terms,reference will now be made the accompanying drawings, wherein:

FIG. 1 depicts an operating environment in accordance with an aspect ofthe present invention;

FIG. 2 schematically depicts a system for collecting and analyzingequipment telematic data in accordance with an aspect of the presentinvention;

FIGS. 3A-3C depict a method for collecting and analyzing equipmenttelematic data in accordance with an aspect of the present invention;and

FIG. 4 depicts an exemplary graphical user interface that may be used toprovide aggregate information in accordance with an aspect of thepresent invention.

DETAILED DESCRIPTION

Embodiments of the present invention will now be described more fullyhereinafter with reference to the accompanying drawings, in which some,but not all, embodiments of the invention are shown. Indeed, theinvention may be embodied in many different forms and should not beconstrued as limited to the embodiments set forth herein; rather, theseembodiments are provided so that this disclosure will satisfy applicablelegal requirements. Where possible, any terms expressed in the singularform herein are meant to also include the plural form and vice versa,unless explicitly stated otherwise. Also, as used herein, the term “a”and/or “an” shall mean “one or more,” even though the phrase “one ormore” is also used herein. Furthermore, when it is said herein thatsomething is “based on” something else, it may be based on one or moreother things as well. In other words, unless expressly indicatedotherwise, as used herein “based on” means “based at least in part on”or “based at least partially on.” Like numbers refer to like elementsthroughout.

An “entity” may be any person or organization implementing a system forcollecting and analyzing equipment telematic data described herein. Theentity may be an organization that performs work in the fields ofelectrical line work, construction, mining, oil or gas drilling,logging, farming, fishing, and the like. A “user” may be any person orentity using a system for collecting and analyzing equipment telematicdata described herein. Often, a user is an employee of the entity. Insome instances, a user of the system may be another computer system orsoftware application that interacts with the system. For example, a usermay be an automated agent that is configured to interact with the systemin order to perform one or more tasks.

As used herein, “equipment” typically refers to vehicles or largemachinery that may be employed in a variety of fields, includingelectrical line work, construction, mining, oil or gas drilling,farming, fishing, and the like. Equipment may include a truck, atrailer, a bucket truck, construction equipment (e.g., a bulldozer, dumptruck, crane, or excavator), a tractor, and the like. Equipment mayinclude sensors for collecting telematic data.

As used herein, “tool” typically refers to an individual item or devicethat may be used to accomplish a particular task related to a variety offields, including electrical line work, construction, mining, oil or gasdrilling, farming, fishing, and the like. A tool may be associated witha piece of equipment. In some instances, a tool may be an integratedcomponent of a piece of equipment, such as the boom and bucket of abucket truck. In some instances, a tool may be a handheld tool ratherthan a component of equipment. Exemplary handheld tools include: drills,saws, load break tools, hot sticks, hammers, clamps, cutting tools,shovels, etc. In some instances, a tool is a device that may be used toperform tasks at a job site and is in communication (e.g., via Bluetoothor other wireless communication) with a piece of equipment. For example,a tool may be a drone in communication with a vehicle.

“Telematic data” refers to data related to the operation of equipment.Telematic data may include data related to the location of equipment,such as GPS coordinates, and/or data related to the location of a toolassociated with the equipment. If the equipment is a vehicle, telematicdata may include data related to the speed and/or heading of thevehicle. Telematic data may include related to the use of toolsassociated with a piece of equipment. In this regard, telematic data mayinclude data related to the use of tools that constitute components ofequipment. For example, telematic data may include data related to theuse of a motor or engine of a piece of equipment, which may indicatethat the equipment is in use. By way of further example, telematic datamay include data related to the use of a power takeoff (PTO) of a pieceof equipment. If the equipment is a vehicle (e.g., a bucket truck), useof a PTO (e.g., to extend a bucket) may indicate that the vehicle is ata work site, rather than merely traveling. Telematic data may alsoinclude sensor data indicating that certain integrated tools of a pieceof equipment are being used. For example, if the equipment is a buckettruck, telematic data may include data from a vehicle sensor indicatingthat the bucket of the bucket truck has been extended for use. Telematicdata may include data related to the use of tools that are handheldtools.

An “equipment telematic dataset” is typically a data file generated by apiece of equipment (e.g., by a telematics device associated with thepiece of equipment) that includes telematic data corresponding to amoment in time. For example, an equipment telematic dataset may include,among other things: an identifier of the applicable equipment (e.g.,name, serial number, or other identifier), location information (e.g.,GPS coordinates) for the equipment, a speed at which the equipment istraveling at that point in time, a travel heading, data related to theuse of an engine/motor of the equipment, data related to the use oftools, such as integrated components of the equipment or handheld tools,and/or a time at which the equipment generated or transmitted thetelematic dataset. A piece of equipment may periodically transmitequipment telematic datasets. In some instances, equipment telematicdatasets may be transmitted at regular intervals (e.g., once per secondor once per minute). A telematics dataset may include information abouta single “event” or multiple “events.” Such “events” may include: achange in speed, a change in heading/direction of travel, and/or use ofcertain components of the equipment (e.g., engine or PTO). A telematicdataset may include information about the events that occurred since thelast telematic dataset was transmitted. In some instances, an equipmenttelematic dataset may be generated and transmitted each time a piece ofequipment (e.g., a telematics device associated with the piece ofequipment) identifies an “event.”

A “job site” typically refers to a location where work is beingperformed by an entity. For example, a job site may be a constructionsite or a location where electrical line work is being performed. If theentity is performing work related to harvesting natural resources (e.g.,mining, oil or gas drilling, logging, farming, or fishing), the job sitemay be the location where such natural resources are harvested.

As used herein, a “yard” typically refers to a location where equipment,tools and/or materials used at a job site may be stored. Beforebeginning work at a job site, employees of an entity may collectequipment, tools, and/or materials to be used at such job site. In someinstances, a yard may be operated by the entity. In other instances, ayard may be operated by a customer for which an entity is tasked toperform work. In some embodiments, the location of a yard may bemanually defined by an entity. In some embodiments, the location of ayard may be determined by analyzing (e.g., via machine learning) thelocation history of multiple pieces of equipment. For example, ifmultiple pieces of equipment have a history of leaving and thenreturning to the same geographic area, such geographic area may bedefined as a “yard.”

The location associated with a yard, job site, or other location may bedefined by a “geo-fence.” A “geo-fence” is a virtual perimeter thatdefines the boundaries of an actual geographic area (e.g., of a yard). Ageo-fence may be defined by centroids, polygons, boundaries, etc. Ageo-fence may be defined manually, through automated logic orcalculations, through machine learning, etc.

In many fields, such as electrical line work, construction, mining, oilor gas drilling, farming, fishing, and the like, it may be desirable totrack the time equipment and personnel are performing work at a jobsite, as opposed to time spent performing other activities, such astraveling, collecting materials at a yard, and taking meal breaks.However, one challenge relating to tracking time performing work at ajob site is determining whether equipment and personnel are located at ajob site. In some instances (e.g., performing construction ormaintenance at a residence), the location of a job site may be readilydefined by a street address. Once the job site has been defined, it maybe possible to track the time equipment and personnel have spent at thejob site by comparing location information (e.g., GPS coordinates) ofsuch equipment and personnel with the defined location of the job site.However, in many fields, such as electrical line work, construction,mining, oil or gas drilling, farming, fishing, and the like, it is notpractical or even possible to define a job site by street address. Forexample, the location of the job sites might not be sufficiently closeto any street address, particularly where the job sites are located inrural or undeveloped areas. By way of further example, where workrelates to repairing or replacing damaged electrical distribution linesand related equipment (e.g., as a result of a storm), the exact locationof the job site(s) (e.g., where the electrical distribution lines aredamaged) might not be known prior to work beginning. Furthermore, evenwhere a particular job site may be correlated with a particular streetaddress, requiring a work crew to provide the correct street address maybe distracting, time consuming, and prone to incorrect entry of thestreet address.

To address these problems, in one aspect, the present invention isdirected to a system for collecting and analyzing equipment telematicdata in order to determine when such equipment is being used at a jobsite. In this regard, the system typically receives periodic telematicdatasets from a piece of equipment. Such telematic datasets typicallyinclude location information (e.g., GPS coordinates) for such equipment.In some embodiments, such telematic datasets may include informationrelated to the location of a tool associated with the equipment. Thelocation of an associated tool may be used as a proxy for the locationof the equipment. By comparing such location information with thelocation of known job sites, the system is able to determine whether, atany particular time, the equipment (as well as personnel associated withsuch equipment) is being used to perform work at a job site or isengaged in other activities (e.g., collecting materials at a yard,traveling to a job site, break time, and the like). By knowing theamount of time spent at a job site, as compared to time spent on otheractivities, the system may determine the productivity of the equipment(as well as personnel associated with such equipment).

Such equipment telematic datasets may also be used to identifypreviously undefined job sites. In this regard, equipment telematicdatasets may include information about the use of various tools, some ofwhich are primarily designed for use at a job site. For instance,equipment telematic datasets may indicate that a vehicle PTO has beenengaged or that a boom of a vehicle (e.g., a bucket truck) has beenextended. Accordingly, the system may analyze equipment telematicdatasets to determine whether integrated tools (e.g., components) of apiece of equipment are being used in a manner indicative of suchequipment being used at a job site. For example, if equipment telematicdatasets indicate that the bucket of a bucket truck has been extended,then the bucket truck is likely being used to perform work at a jobsite. In another instance, equipment telematic datasets may indicatethat handheld tools associated with a piece of equipment are being used.For example, a handheld tool (e.g., a hammer) may have an RFID tag andthe equipment may have an RFID sensor for sensing whether the handheldtool is present at the vehicle or whether the handheld tool has movedpassed the sensor. If the RFID sensor does not sense the RFID tag (orhas sensed that the tool has left the vehicle by the RFID tag beingdetected in the proximity of an RFID sensor by a door of the equipment),then such handheld tool is likely being used at a job site. If tools(e.g., handheld tools or integrated components of equipment) are beingused in such a manner, but such equipment is not located at a previouslydefined job site, then the system may define the current location ofsuch equipment as a new job site. Accordingly, the system, among otherthings, is able to automatically determine the locations of job sites,and then use such locations to determine whether, at any given time,equipment (as well as personnel associated with such equipment) is beingused to perform work at a job site.

Telematic data may also be combined with other information in equipmentrecords. Such other information may include: identities of personnelassociated with (e.g., assigned to) such equipment, such as the leaderof a crew assigned to use the equipment; the number of worked hourssubmitted by such personnel (e.g., on a timesheet); a project identifier(e.g., project number) for which the equipment was used during theapplicable time period; a line of business of an entity for which theequipment was used during the applicable time period; the type of workperformed by the equipment and/or personnel; a geographic region inwhich the applicable yard and job site are located; and an identity of acustomer for which work was performed by the equipment and/or personnel.Such equipment records may then be analyzed in connection with providingvarious functions. The system may analyze the job site locations in theequipment records to determine whether to update drawings or schematicsmaintained by an entity. In some embodiments, aggregate information maybe used to identify trends and project future needs or problems.

FIG. 1 provides a block diagram illustrating an operating environment100, in accordance with an embodiment of the present invention. Asillustrated in FIG. 1 , the operating environment 100 typically includesmultiple pieces of equipment 150, illustrated by way of example in FIG.1 as a truck 150A, a trailer 150B, and a tractor 150C. The equipment 150may be able to generate and transmit equipment telematic datasets thatinclude telematic data related to such equipment 150. Accordingly, eachpiece of equipment 150 may include one or more sensors (e.g., sensorsfor sensing the location, speed, heading, performance of integratedcomponents, etc. of the equipment) for collecting telematic data, acontroller for aggregating such telematic data and generating equipmenttelematic datasets, and a network interface for communicating suchequipment telematic datasets. For example, the truck 150A may include atelematics device that connects to the truck's engine control module(ECM), as well as other sensors, and obtains GPS location data for thetruck.

The operating environment 100 also typically includes a system 200 forcollecting and analyzing equipment telematic data transmitted by theequipment 150. The system 200 and the equipment 150 are typically incommunication with a network 110, such as the Internet, wide areanetwork, local area network, wireless telephone network, Bluetoothnetwork, near field network, or any other form of contact or contactlessnetwork. One or more users, each having a user computing device 120,such as a PC, laptop, mobile phone, tablet, television, mobile device,or the like, may be in communication with the system 200 via the network110. In some embodiments, a user may be another computer system orsoftware application that interacts with the system to perform one ormore tasks. The system 200 may be in communication with other entitysystems 160 (e.g., an enterprise resource planning (ERP) system), aswell as various third party systems 170. In some embodiments, a thirdparty system 170 collects telematic data transmitted by the equipment150, and then the system 200 obtains this telematic data from such thirdparty system 170.

FIG. 2 depicts the system 200 in more detail. As depicted in FIG. 2 ,the system 200 typically includes various features such as a networkcommunication interface 210, a processing device 220, and a memorydevice 250. The network communication interface 210 includes a devicethat allows the system 200 to communicate with the equipment 150, usercomputing devices 120 (e.g., over the network 110 (shown in FIG. 1 )),other entity systems 160, and/or third party systems 170.

As used herein, a “processing device,” such as the processing device220, generally refers to a device or combination of devices havingcircuitry used for implementing the communication and/or logic functionsof a particular system. For example, a processing device 220 may includea digital signal processor device, a microprocessor device, and variousanalog-to-digital converters, digital-to-analog converters, and othersupport circuits and/or combinations of the foregoing. Control andsignal processing functions of the system are allocated between theseprocessing devices (e.g., processors) according to their respectivecapabilities. The processing device 220 may further includefunctionality to operate one or more software programs based oncomputer-executable program code thereof, which may be stored in amemory. As the phrase is used herein, a processing device 220 may be“configured to” perform a certain function in a variety of ways,including, for example, by having one or more general-purpose circuitsperform the function by executing particular computer-executable programcode embodied in computer-readable medium, and/or by having one or moreapplication-specific circuits perform the function.

As used herein, a “memory device,” such as the memory device 250,generally refers to a device or combination of devices that store one ormore forms of computer-readable media for storing data and/orcomputer-executable program code/instructions. Computer-readable mediais defined in greater detail below. For example, in one embodiment, thememory device 250 includes any computer memory that provides an actualor virtual space to temporarily or permanently store data and/orcommands provided to the processing device 220 when it carries out itsfunctions described herein.

As noted, the system 200 is configured to collect and analyze telematicdata generated by the equipment 150 as described in more detail herein.Accordingly, the system 200 typically includes one or more modulesstored in the memory device 250, which facilitate such analysis. Asdepicted in FIG. 2 , the system 200 typically includes an analysismodule 255 configured to perform such analysis.

In connection with its analysis of telematic data from the equipment150, the system 200 typically generates equipment records. An “equipmentrecord” typically includes information related to the use of aparticular piece of equipment during a particular time period (e.g.,during a particular day). An equipment record typically includesinformation related to the amount of time a piece of equipment spends inconnection with various activities/locations (e.g., amount of time spentat a job site, yard, traveling, and the like). An equipment record mayalso include information related to the personnel using the equipment,the yard to which such equipment is assigned, the identity of projectsworked on by the equipment/personnel, the tasks completed by theequipment/personnel during the time period, delays experienced duringthe time period, mileage, and weather during the time period. Equipmentrecords generated by the system 200 may be stored in an equipment recorddatabase 260. Information associated with known job sites may be storedin a job site database 265

FIGS. 3A-3C, depict a method 300 of collecting and analyzing telematicdata generated by a piece of equipment during a particular time periodin accordance with an embodiment of the present invention. This method300 may be performed by the system 200. The steps of the method 300 maybe repeated for the same piece of equipment during different timeperiods, as well as for different pieces of equipment (during the sameor different time periods).

At block 305, the method 300 includes collecting one or more telematicdatasets related to a particular piece of equipment. In someembodiments, the equipment transmits the telematic datasets to a thirdparty system, which then may transmit or make available (e.g., via anonline portal) the telematic datasets to the system 200. Alternatively,these telematic datasets may be transmitted by the equipment directly tothe system 200. The telematic datasets may be associated with aparticular time period (e.g., the same day), and each piece of equipmentmay periodically transmit telematic datasets to the system 200 duringsuch time period.

At block 310, an equipment record is created for the piece of equipmentif a corresponding equipment record does not yet exist, and suchequipment record may be stored in the equipment record database 260.This equipment record may be initially populated with an identifier ofthe equipment (e.g., name, serial number, etc.) as well as informationregarding the applicable time period (e.g., a particular day).

At block 315, the telematic datasets are analyzed to determine whichtelematic datasets are associated with a yard. In this regard, eachtelematic dataset typically includes information related to the locationof the equipment when the telematic dataset is transmitted by theequipment. This location information (e.g., longitude and latitude, GPScoordinates, and the like) is typically parsed from the telematicdataset and compared to location information for defined yards. Thislocation information may relate to the location of a tool associatedwith the equipment, such that the location of the associated tool may beused as a proxy for the location of the equipment. If the locationinformation of a telematic dataset corresponds to a particular yard(e.g., GPS coordinates within a telematic dataset are within a geo-fenceassociated with a particular yard), then such telematic dataset isassociated with (e.g., assigned to) such yard and may be considered tobe a “yard telematic dataset.” Any telematic dataset that is notassociated with a yard may be considered to be a “non-yard telematicdataset.”

At block 320, the telematic datasets associated with a yard are analyzedto determine the total amount of time the piece of equipment has spentin a yard during the applicable time period. In this regard, eachtelematic dataset may include a timestamp indicating when such telematicdataset was generated or transmitted by the equipment. Based on thetimestamps of the telematic datasets associated with a yard, the system200 may be able to calculate the total time the piece of equipment hasspent in a yard during the applicable time period. This total yard timemay be included in the applicable equipment record.

At block 325, it is determined whether there are any yard telematicdatasets (i.e., telematic datasets associated with a yard) that relateto the equipment record.

If there are yard telematic datasets that relate to the equipmentrecord, then, at block 330, the yard of the first (e.g., earliest) yardtelematic dataset is typically designated as the “yard” of the equipmentrecord, and the equipment record may be updated accordingly.

If there are no yard telematic datasets that relate to the equipmentrecord, then, at block 335, the yard of a previous equipment record(i.e., an equipment record associated with the same piece of equipmentfor an earlier time period) is typically assigned to be the “yard” ofthe equipment record. For example, the system may identify the equipmentrecord for the equipment during a prior time period (e.g., theimmediately preceding day or week) and define the yard of such equipmentrecord as the yard of the current equipment record.

Next, the method 300 proceeds to the steps depicted in FIG. 3B, whichrelate to identifying new job sites. At block 340, the non-yardtelematic datasets for the equipment are analyzed to determine if a jobsite condition has been satisfied. A job site condition is a condition(or set of conditions) that may be determined from the telematicdatasets and which is indicative of the equipment being located at a jobsite. In some embodiments, a job site condition may be satisfied if aparticular tool (e.g., an integrated component of equipment or ahandheld tool) associated with the equipment has been used. Typically,such a condition relates to the use of a tool that is primarily designedfor use on a job site. For example, a job site condition for a buckettruck may be satisfied if the PTO of the bucket truck has been engagedand/or a boom of the bucket truck has been extended. By way of furtherexample, the equipment may be able to sense use of a handheld tool andsuch use may satisfy a job site condition. For example, the handheldtool may be in wireless communication with the equipment (e.g., via aBluetooth connection), and the handheld tool may transmit a notificationto the equipment that the handheld tool has been turned on or used. Byway of further example, the equipment may be able to sense whether thetool is located within the equipment (e.g., by sensing or not sensing anRFID tag attached to the tool or determining that the equipment has losta Bluetooth connection with the tool), and, if the tool is not locatedwithin the vehicle, the tool may be presumed to be in use. In someembodiments, there may be job site conditions that do not require use oftools to be satisfied. For example, another job site condition for abucket truck may be satisfied if (i) the bucket truck has stopped for atleast a defined period of time (e.g., at least five or ten minutes) and(ii) the bucket truck is not located at a defined non-yard site, such asnot being located at a restaurant, gas station, hardware store, or thelike. In some embodiments, job site conditions may be predefined by theentity. In some embodiments, job site conditions may be automaticallydetermined by analyzing (e.g., through machine learning and/or naturallanguage processing) previous telematic data, equipment records, andother data to identify tool uses indicative of job site locations.

If machine learning is used to determine job site conditions, a trainingset based on a large number (e.g., 1,000) equipment records may be usedto initially train a machine learning algorithm to identify non-yardtelematic datasets that satisfy known job site conditions. Once themachine learning algorithm has been trained, the machine learningalgorithm may be used to determine whether a job site condition has beensatisfied in subsequent non-yard telematic datasets. If the machinelearning algorithm has a likelihood of being accurate that is above adefined threshold (e.g., 60% or 80%) then the machine learning algorithmmay be used to determine whether a job site condition exists. On theother hand, if the machine learning algorithm has a likelihood of beingaccurate that is below a defined threshold, then conditional logic asdescribed in the preceding paragraph may be used to determine whetherthe job site condition exists.

In some embodiments, the determination of whether a job site conditionexists may be based at least on part on image data received from theequipment. In this regard, the equipment may provide images as part of,or in parallel with, the telematic datasets. These images may becaptured from one or more cameras mounted to the equipment. The imagesmay then be analyzed to identify objects that may be indicative of a jobsite condition generally (e.g., poles, cones, electrical equipment,wires, construction equipment, and the like) or indicative of a specificjob site (e.g., features uniquely associated with a known job site).Machine learning may be employed to identify objects in images, as wellas to identify objects and features indicative of a job site. Knownthird party services, such as Microsoft's Computer Visions(https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/)and Google's Vision AI (https://cloud.google.com/vision/), may be usedto process such images to search for images that may be associated witha job site condition.

Similar to the determination of whether a job site condition exists,machine learning and/or images obtained from the equipment may also beemployed to determine whether telematic datasets are associated with ayard.

If a job site condition has been satisfied, then, at block 345, it isdetermined whether the location of the equipment while the job sitecondition was satisfied is within an existing job site. The location ofexisting job sites may be determined by retrieving location informationfor existing job sites from the job site database 265.

If the location of the equipment while the job site condition wassatisfied is not within an existing job site, then, at block 350, suchlocation is designated a job site location and added to the job sitedatabase 265. In some embodiments, the system may designate the locationof such new job site as being the area within defined distance (e.g.,within 100-300 feet) of the location of the equipment at the time thejob site condition was satisfied. In some instances, the system 200 maydefine a geo-fence corresponding to the location of the new job site.

Next, the method 300 proceeds to the steps depicted in FIG. 3C. At block355, the non-yard telematic datasets are analyzed to determine whichtelematic datasets are associated with a job site. In some embodiments,if the location information of a telematic dataset corresponds to aparticular job site (e.g., GPS coordinates within a telematic datasetare within a geo-fence associated with a particular job site), then suchtelematic dataset is associated with (e.g., assigned to) such job site.Similar to the determination of whether a job site condition exists,machine learning and/or images obtained from the equipment may beemployed to determine which telematic datasets are associated with a jobsite.

At block 360, the remaining non-yard telematic datasets (i.e., thosenon-yard telematic datasets not associated with a job site) are analyzedto determine which telematic datasets are associated with otheractivities/locations. For example, the system 200 may determine whetherthe location information of each remaining non-yard telematic datasetcorresponds to the location of a gas station, restaurant, or hardwarestore, and, if so, such telematic dataset may be designated a “gas”telematic dataset, “restaurant” telematic dataset, or “hardware”telematic dataset. Any still-remaining non-yard telematic datasets(i.e., those non-yard telematic datasets not associated with a job siteor other location, such as a gas station, restaurant, or hardware store)may be designed as “travel” telematic datasets. In addition to or as analternative to the categories of “gas”, “restaurant”, “hardware”, and“travel”, the system 200 may be configured to determine whetherremaining non-yard telematic datasets are associated with otheractivities/locations. Similar to the determination of whether a job sitecondition exists, machine learning and/or images obtained from theequipment may be employed to determine the type of activity (e.g.,“gas”, “restaurant”, “hardware”, or “travel”) associated with theremaining non-yard telematic datasets.

At block 365, the telematic datasets associated with a job site areanalyzed to determine the total amount of time the piece of equipmenthas spent at a job site during the applicable time period. In thisregard, each telematic dataset may include a timestamp indicating whensuch telematic dataset was generated or transmitted by the equipment.Based on the timestamps of the telematic datasets associated with a jobsite, the system 200 may be able to calculate the total time the pieceof equipment has spent at a job site during the applicable time period.This total job site time may be included in the applicable equipmentrecord, which, as described in more detail below, may be used, forexample, in calculating various productivity metrics and identifyinganomalies.

At block 370, the telematic datasets associated with otheractivities/locations (i.e., those telematic datasets associated withneither a job site nor yard) are analyzed to determine the total amountof time the piece of equipment has spent in connection with such otheractivities/locations during the applicable time period. For example, thesystem 200 may determine the total “gas” time, “restaurant” time,“hardware” time, and “travel” time for the equipment during theapplicable time period. The applicable equipment record may then beupdated to include the time related to any applicable categories ofother activities/locations (e.g., “gas” time, “restaurant” time,“hardware” time, “travel” time, etc.).

At block 375, other information related to the equipment may becollected (e.g., from the other entity system(s) 160) and added to theapplicable equipment record. For example, such other information mayinclude: identities of personnel associated with such equipment, such asthe leader of a crew assigned to use the equipment; the amount of workedhours submitted by such personnel (e.g., on a timesheet); a projectidentifier (e.g., project number) for which the equipment was usedduring the applicable time period; a line of business of the entity forwhich the equipment was used during the applicable time period; the typeof work performed by the equipment and/or personnel; a geographic orother region in which the applicable yard and job site are located; andan identity of a customer for which work was performed by the equipmentand/or personnel. In this regard, timesheets submitted by work crews andother data collected by the other entity systems 160 may identify theequipment used by the work crew, as well as the hours worked, tasksperformed, delays experienced, etc. by the work crew, therebyfacilitating the association of such crew information with the identityof the equipment.

By way of further example, where the piece of equipment is a vehicle,the total mileage traveled by such equipment during the applicable timeperiod may be added to the applicable equipment record. Such otherinformation may include an indication of whether the work performed bythe equipment and/or personnel is associated with an emergency event(e.g., the work is being performed to repair damage from a naturaldisaster, such as a storm). Such other information may includeweather-related information (e.g., temperature and amount ofprecipitation), which may be received by a data feed provided by a thirdparty system 170. Such other information may include information aboutdelays experienced by the equipment and/or personnel during theapplicable time period, such as the type(s) of delay and amount of delaytime. In this regard, a crew leader may submit such delay information(e.g., to the system 200 or to another entity system). Such otherinformation may include information about the tasks performed by theequipment and/or personnel during the applicable time period, such asthe types of tasks performed and the quantity of such tasks performed.For example, in the field of electrical line work such task informationmay identify the number of transformers or poles replaced during aparticular time period. As noted, much of this other information may becollected from the other entity system(s) 160. Such information may beprovided to such other entity system(s) 160 by personnel (e.g., a crewleader) associated with the equipment, such as in connection with suchpersonnel completing timesheets and/or work orders for the entity.

As noted above, this method 300 for collecting and analyzing equipmentmay be repeated for the same piece of equipment during different timeperiods, as well as for different pieces of equipment (during the sameor different time periods). Accordingly, the system 200 may generateequipment records for various pieces of equipment for different timeperiods. Once equipment records have been created, the system 200 may beconfigured to analyze such equipment records to provide usefulinformation to the entity. For example, such information may be used tocalculate various productivity metrics, identify anomalies, and thelike.

In some embodiments, equipment records may be analyzed by the system 200to identify potential anomalies. For example, each equipment record maybe analyzed to determine if there is a discrepancy between the totalnumber of telematic time associated with the applicable piece ofequipment and the total time submitted by assigned personnel (e.g.,timesheet hours). If there is a discrepancy between the total telematictime (e.g., “yard” time, “job site” time, “gas” time, “restaurant” time,“hardware” time, and “travel” time for the equipment during theapplicable time period) and personnel time (e.g., a discrepancy ofgreater than ten percent or twenty percent), the system 200 may flag theequipment record and/or time sheet as having an anomaly, which mayindicate that the equipment record and/or time sheet has incorrect data.The system 200 also may flag the equipment record as having an anomalyif the total amount of personnel time or telematic time during theapplicable time period is below or above a defined threshold. In someembodiments, each equipment record may be analyzed to determine if thetotal time during the applicable time period associated with one or morenon-job-site activities (e.g., “yard” time, “gas” time, “restaurant”time, “hardware” time, and/or “travel” time) exceeds a definedthreshold, and, if so, the system 200 may flag the equipment record ashaving an anomaly. For example, the total number of “yard” hours exceedsa defined threshold, then the equipment and personnel may have spent toomuch time in a yard during the applicable time period. In someembodiments, the system 200 may determine whether multiple pieces ofequipment associated with particular personnel (e.g., a crew leader)during a particular time period are all assigned to the same yard. Ifpieces of equipment associated with particular personnel (e.g., a crewleader) during a particular time period are assigned to different yards,then such personnel and/or yards may have been incorrectly associatedwith such equipment, and so the system 200 may flag the applicableequipment records. In some embodiments, the system 200 may transmit analert to one or more users regarding any flagged equipment records sothat such users may further investigate the cause of the flaggedanomalies.

In some embodiments, the system 200 may analyze the job site locationsin the equipment records to determine whether to update drawings orschematics maintained by the entity. In this regard, the entity maymaintain engineering drawings or similar schematics indicating thelocation of structures, devices, and/or the like that have beenconstructed and/or maintained by the entity. Based on job site locationand other information contained in equipment records, the system 200 maydetermine that construction and/or maintenance work was performed at aparticular location. If such location is not consistent with (e.g.,match) engineering drawings or similar schematics of the entity, thesystem 200 may automatically update such engineering drawings or similarschematics to include the correct location and/or flag such engineeringdrawings or similar schematics for further review by a user.

In some embodiments, equipment records may be analyzed by the system 200to determine aggregate productivity and other information related tovarious pieces of equipment and personnel. For example, the system 200may determine aggregate information related to the total time spent at ajob site, at a yard, or performing other activities (e.g., “gas”,“restaurant”, “hardware”, and “travel” time). The system 200 maydetermine aggregate information related to the quantity of tasksperformed. The system 200 may determine aggregate information related tothe types and amount of delay experienced. Information may be aggregatedfor: a single piece of equipment over multiple time periods (e.g., overmultiple days); individual personnel (e.g., a crew leader) or a group ofpersonnel (e.g., a crew) over multiple time periods; a yard over asingle time period (e.g., day) or multiple time periods (e.g., byaggregating all equipment records assigned to such yard); a geographicregion; a customer; or based on other collected information. Forexample, the system 200 may determine the average daily “yard,” “jobsite,” and “travel time” for a piece of equipment over a week or month.The system 200 may determine the average daily delay time acrossdifferent categories of delay experienced by a crew over a week ormonth. By way of further example, the system 200 may determine theaverage daily productivity (e.g., average quantity of various tasks) ofall equipment assigned to a particular yard during a particular month.The system 200 may compare the productivity of different individuals andcrews to determine which individuals and/or crews are more or lessefficient. Based on the relative efficiency of different individualsand/or crews, such individuals and/or crews may be assigned differenttasks or prompted to perform additional training.

This aggregate information may be provided to one or more users (e.g.,employees of the entity). In some instances, this aggregate informationmay be provided to customers of the entity. In some embodiments,aggregate information may be delivered to or accessible via a user'smobile device (e.g., smartphone or tablet computer). In someembodiments, this aggregate information may be accessible via anInternet-accessible portal providing such information in a graphicaluser interface. Such portal may allow users to make queries and generatereports and graphical presentations. In some embodiments, such portaland the information available may be customized for different customers.In other embodiments, reports based on the aggregate information may beprovided to user based on predefined templates. In some embodiments,this aggregate information may be presented to users in the form of aheat map.

FIG. 4 depicts an exemplary graphical user interface that may be used toprovide aggregate information. The graphical user interface depicted inFIG. 4 allows a user to select a time period (e.g., week or month),yard, and crew work type for which the user desires to see aggregateinformation. For the selected time period, yard, and crew work type, thegraphical user interface provides: the quantity of crews, average yard,job, and travel time, information about the quantity of tasks completed,and information about experienced delays.

In some instances, customers of the entity may allocate costs of work todifferent cost centers (e.g., “operations and maintenance” versus“capital” costs). In some embodiments, the system may analyze aggregateinformation contained in equipment records (e.g., by analyzinginformation such as a project identifier; the type of work performed;and an identity of a customer), to determine the aggregate costs relatedto different customer cost center. Accordingly, the system may be ableto generate a report detailing “operations and maintenance” versus“capital” costs (as well as associated tasks completed) for a particularcustomer. Such report may then be provided to such customer.

In some embodiments, aggregate information may be used to identifytrends and project future needs or problems. For example, the aggregateinformation be able to identify trends in the types of work performed bythe entity, such as by season, location, or geographic region, which maybe used to project future work expectations. Based on future workexpectations, the system 200 may be able to suggest locations for newyards (e.g., that would reduce costs and/or travel time to expectedfuture work), as well as the types and volume of equipment and materialsneeded to meet such future work expectations. Aggregate information maybe analyzed to identify variables (e.g., weather, location, traffic,personnel, etc.) that drive productivity or delays. Based on variablesdetermined to cause delays, the system 200 may be able to projectexpected delays for future projects. For example, if telematic dataindicates that travel time is unexpectedly high for projects within agiven region, then this information can be used in determining expecteddelays (and associated costs) for other projects in the same region. Insome embodiments, the system 200 may analyze the history of workperformed to address prior natural disasters (e.g., storms) to projectthe amount and location of work that will need to be performed to repairdamage from a similar expected natural disaster. Based on such projectedwork and the expect path of such expected natural disaster, the entitymay be able to pre-stage equipment and personnel to more promptly repairdamage.

In some embodiments, the system 200 may calculate the estimatedproductivity (e.g., expected quantity of various tasks) for particularequipment or personnel over a particular time period and compare theestimated productivity to the actual productivity (e.g., actual quantityof various tasks completed). The estimated productivity may be based onthe average productivity across the entity, adjusted for various factorssuch as weather, delays, job site time, geographic region, yard, crewleader, and/or the like that may affect productivity. In this regard,regression analysis may be performed by the system 200 to create a modelfor calculating estimated productivity. The system 200 may then provideusers with information regarding the estimated productivity and actualproductivity (e.g., for a piece of equipment, group of personnel, typeof task, etc.). In some embodiments, the system may be configured tocalculate efficiency scores for personnel and equipment. Where theactual productivity for equipment or personnel exceeds the estimatedproductivity, such equipment or personnel may have a relatively highefficiency score, whereas if the actual productivity for equipment orpersonnel is below the estimated productivity, such equipment orpersonnel may have a relatively low efficiency score.

As described above, the system described herein may be used in a varietyof fields, including electrical line work. The system may be useful inthe construction industry. For example, an entity may have multipleforemen and project operating at the same time, and so the system couldbe used to track multiple crews based on location and tool usage todetermine time at the construction site and what was being done based onthe tools used. The system may also be useful in the logging industry.In this regard, the system may track and determine that logging wasperformed within the bounds of an area allotted to logging and that thecorrect trees were harvested. The system may also be able used for (i)identify safety improvements based on tracking tool/equipment usage andsafety incidents reported and (ii) tracking the planting, growth, andharvesting of tree having RFID tags. In the fishing industry, the systemmay be used to track where nets are dropped and how much is caught, aswell as various data such as weather data, ocean temperature, and thelike. Based on this historic data as well as current data, the systemmay be able to predict catch amounts. With respect to cleaning,maintenance, and similar services, the system could be used to trackspent at a job site (e.g., based on usage of RFID tagged tools, arrivaltime, etc.).

As evident from the preceding description, the system described hereinrepresents an improvement in current technology. As described above,there are various problems associated with identifying the location of ajob site. Accordingly, the system typically receives telematic data froma piece of equipment, including location information, as well asinformation about the use of various tools associated with suchequipment that are primarily designed for use at a job site.Accordingly, the system may analyze such telematic data to determinewhether tools are being used in a manner indicative of such equipmentbeing used at a job site. If such tools are being used in such a manner,then the system knows that such equipment is located at a job site.Accordingly, if such equipment is not located at a previously definedjob site, then the system may define the current location of suchequipment as a new job site. Therefore, the system may be able toautomatically determine the locations of job sites, and then use suchlocations to determine whether, at any given time, equipment (as well aspersonnel associated with such equipment) is being used to perform workat a job site. Accordingly, the system provides a technical solution forovercoming the problem of how to automatically identify new job sites.

As will be appreciated by one of skill in the art, the present inventionmay be embodied as a method (including, for example, acomputer-implemented process, a business process, and/or any otherprocess), apparatus (including, for example, a system, machine, device,computer program product, and/or the like), or a combination of theforegoing. Accordingly, embodiments of the present invention may takethe form of an entirely hardware embodiment, an entirely softwareembodiment (including firmware, resident software, micro-code, and thelike), or an embodiment combining software and hardware aspects that maygenerally be referred to herein as a “system.” Furthermore, embodimentsof the present invention may take the form of a computer program producton a computer-readable medium having computer-executable program codeembodied in the medium.

Any suitable transitory or non-transitory computer readable medium maybe utilized. The computer readable medium may be, for example but notlimited to, an electronic, magnetic, optical, electromagnetic, infrared,or semiconductor system, apparatus, or device. More specific examples ofthe computer readable medium include, but are not limited to, thefollowing: an electrical connection having one or more wires; a tangiblestorage medium such as a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), a compact discread-only memory (CD-ROM), or other optical or magnetic storage device.

In the context of this document, a computer readable medium may be anymedium that can contain, store, communicate, or transport the programfor use by or in connection with the instruction execution system,apparatus, or device. The computer usable program code may betransmitted using any appropriate medium, including but not limited tothe Internet, wireline, optical fiber cable, radio frequency (RF)signals, or other mediums.

Computer-executable program code for carrying out operations ofembodiments of the present invention may be written in an objectoriented, scripted or unscripted programming language. However, thecomputer program code for carrying out operations of embodiments of thepresent invention may also be written in conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages.

Embodiments of the present invention are described above with referenceto flowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products. It will be understood thateach block of the flowchart illustrations and/or block diagrams, and/orcombinations of blocks in the flowchart illustrations and/or blockdiagrams, can be implemented by computer-executable program codeportions. These computer-executable program code portions may beprovided to a processor of a general purpose computer, special purposecomputer, or other programmable data processing apparatus to produce aparticular machine, such that the code portions, which execute via theprocessor of the computer or other programmable data processingapparatus, create mechanisms for implementing the functions/actsspecified in the flowchart and/or block diagram block or blocks.

These computer-executable program code portions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the code portions stored in the computer readablememory produce an article of manufacture including instructionmechanisms which implement the function/act specified in the flowchartand/or block diagram block(s).

The computer-executable program code may also be loaded onto a computeror other programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer-implemented process such that the codeportions which execute on the computer or other programmable apparatusprovide steps for implementing the functions/acts specified in theflowchart and/or block diagram block(s). Alternatively, computer programimplemented steps or acts may be combined with operator or humanimplemented steps or acts in order to carry out an embodiment of theinvention.

As the phrase is used herein, a processor may be “configured to” performa certain function in a variety of ways, including, for example, byhaving one or more general-purpose circuits perform the function byexecuting particular computer-executable program code embodied incomputer-readable medium, and/or by having one or moreapplication-specific circuits perform the function.

Embodiments of the present invention are described above with referenceto flowcharts and/or block diagrams. It will be understood that steps ofthe processes described herein may be performed in orders different thanthose illustrated in the flowcharts. In other words, the processesrepresented by the blocks of a flowchart may, in some embodiments, be inperformed in an order other that the order illustrated, may be combinedor divided, or may be performed simultaneously. It will also beunderstood that the blocks of the block diagrams illustrated, in someembodiments, merely conceptual delineations between systems and one ormore of the systems illustrated by a block in the block diagrams may becombined or share hardware and/or software with another one or more ofthe systems illustrated by a block in the block diagrams. Likewise, adevice, system, apparatus, and/or the like may be made up of one or moredevices, systems, apparatuses, and/or the like. For example, where aprocessor is illustrated or described herein, the processor may be madeup of a plurality of microprocessors or other processing devices whichmay or may not be coupled to one another. Likewise, where a memory isillustrated or described herein, the memory may be made up of aplurality of memory devices which may or may not be coupled to oneanother.

While certain exemplary embodiments have been described and shown in theaccompanying drawings, it is to be understood that such embodiments aremerely illustrative of, and not restrictive on, the broad invention, andthat this invention not be limited to the specific constructions andarrangements shown and described, since various other changes,combinations, omissions, modifications and substitutions, in addition tothose set forth in the above paragraphs, are possible. Those skilled inthe art will appreciate that various adaptations and modifications ofthe just described embodiments can be configured without departing fromthe scope and spirit of the invention. Therefore, it is to be understoodthat, within the scope of the appended claims, the invention may bepracticed other than as specifically described herein.

The invention claimed is:
 1. A system comprising: a piece of equipment, wherein the piece of equipment is a piece of construction equipment, the piece of construction equipment comprising one or more sensors that collect telematic data associated with the piece of construction equipment; and a system for collecting and analyzing equipment telematic data, comprising: a computer apparatus including one or more processors, a memory, and a network communication interface; and an analysis module stored in the memory, executable by the one or more processors and configured for: receiving, via the network communication interface, telematic data from the piece of equipment; parsing the telematic data to identify (i) location information and (ii) usage information for one or more tools associated with the equipment; analyzing the telematic data to determine whether a job site condition has been satisfied; determining that the job site condition has been satisfied; determining that a first job site location of the equipment is a new job site in response to (1) determining that the job site condition has been satisfied, wherein determining that the job site condition has been satisfied comprises determining that the one or more tools have been used, (2) identifying the first job site location based on the location information of the telematic data, (3) retrieving location information for existing job sites from a job site database, and (4) determining that the first job site location is not within one of the existing job sites, wherein the one or more tools comprises a handheld tool, wherein determining that the one or more tools have been used comprises: detecting, from the telematic data, that the handheld tool has lost a wireless connection to the equipment; based on detecting that the handheld tool has lost the wireless connection to the equipment, determining that the handheld tool has left the equipment; and based on detecting that the handheld tool has left the equipment, determining that the handheld tool is in use; in response to determining that the first job site location is a new job site, updating the job site database to include the first job site location; generating aggregated data based on the telematic data and an equipment record associated with the piece of equipment; and presenting the aggregated data on a user computing device through a portal comprising a graphical user interface, wherein the portal is configured to allow a user to generate a report associated with the piece of equipment, wherein the report includes information related to time spent by the piece of equipment at one or more job site locations in the job site database, the one or more job site locations including the first job site location.
 2. The system according to claim 1, wherein analyzing the telematic data to determine whether a job site condition has been satisfied comprises using a machine learning algorithm to determine whether the job site condition has been satisfied.
 3. The system according to claim 1, wherein the analysis module is configured for: receiving, via the network communication interface, image data from the piece of equipment; and analyzing the image data; wherein determining that the job site condition has been satisfied is based at least in part on analyzing the image data.
 4. The system according to claim 3, wherein analyzing the image data comprises identifying one or more objects associated with the job site condition.
 5. The system according to claim 1, wherein the telematic data comprises a plurality of telematic datasets.
 6. The system according to claim 5, wherein the analysis module is configured for determining an activity and/or location associated with each of the telematic datasets.
 7. The system according to claim 6, wherein the analysis module is configured for determining a total time the piece of equipment is associated with each of a plurality of activities and/or locations.
 8. The system according to claim 6, wherein the analysis module is configured for determining a total time the piece of equipment spent at the first job site location during a defined time period.
 9. The system according to claim 1, wherein determining that the job site condition has been satisfied comprises detecting (1) that the equipment is stationary for a defined period of time and (2) that the equipment is not located at a defined job site or non-yard site, wherein the non-yard site is a restaurant, gas station, or store.
 10. A computer implemented method for collecting and analyzing equipment telematic data, comprising: receiving, via one or more computer processors, telematic data from a piece of equipment, wherein the piece of equipment is a piece of construction equipment, the piece of construction equipment comprising one or more sensors that collect telematic data associated with the piece of construction equipment; parsing, via one or more computer processors, the telematic data to identify (i) location information and (ii) usage information for one or more tools associated with the equipment; analyzing, via one or more computer processors, the telematic data to determine whether a job site condition has been satisfied; determining, via one or more computer processors, that the job site condition has been satisfied; determining that a first job site location of the equipment is a new job site in response to (1) determining that the job site condition has been satisfied, wherein determining that the job site condition has been satisfied comprises determining that the one or more tools have been used, (2) identifying the first job site location based on the location information of the telematic data, (3) retrieving location information for existing job sites from a job site database, and (4) determining that the first job site location is not within one of the existing job sites, wherein the one or more tools comprises a handheld tool, wherein determining that the one or more tools have been used comprises: detecting, from the telematic data, that the handheld tool has lost a wireless connection to the equipment; based on detecting that the handheld tool has lost the wireless connection to the equipment, determining that the handheld tool has left the equipment; and based on detecting that the handheld tool has left the equipment, determining that the handheld tool is in use; in response to determining that the first job site location is a new job site, updating the job site database to include the first job site location; generating aggregated data based on the telematic data and an equipment record associated with the piece of equipment; and presenting the aggregated data on a user computing device through a portal comprising a graphical user interface, wherein the portal is configured to allow a user to generate a report associated with the piece of equipment, wherein the report includes information related to time spent by the piece of equipment at one or more job site locations in the job site database, the one or more job site locations including the first job site location.
 11. The method according to claim 10, wherein analyzing the telematic data to determine whether a job site condition has been satisfied comprises using a machine learning algorithm to determine whether the job site condition has been satisfied.
 12. The method according to claim 10, comprising: receiving, via a network communication interface, image data from the piece of equipment; and analyzing the image data; wherein determining that the job site condition has been satisfied is based at least in part on analyzing the image data.
 13. The method according to claim 12, wherein analyzing the image data comprises identifying one or more objects associated with the job site condition.
 14. The method according to claim 10, wherein the telematic data comprises a plurality of telematic datasets.
 15. The method according to claim 14, comprising determining an activity and/or location associated with each of the telematic datasets.
 16. The method according to claim 15, comprising determining a total time the piece of equipment is associated with each of a plurality of activities and/or locations.
 17. The method according to claim 15, comprising determining a total time the piece of equipment spent at the first job site location during a defined time period.
 18. A computer program product for collecting and analyzing equipment telematic data, wherein the computer program product comprises a non-transitory computer-readable medium comprising computer-readable instructions, the computer-readable instructions, when executed by a computer processor, cause the computer processor to perform the steps of: receiving telematic data from a piece of equipment, wherein the piece of equipment is a piece of construction equipment, the piece of construction equipment comprising one or more sensors that collect telematic data associated with the piece of construction equipment; parsing the telematic data to identify (i) location information and (ii) usage information for one or more tools associated with the equipment; analyzing the telematic data to determine whether a job site condition has been satisfied; determining that the job site condition has been satisfied; determining that a first job site location of the equipment is a new job site in response to (1) determining that the job site condition has been satisfied, wherein determining that the job site condition has been satisfied comprises determining that the one or more tools have been used, (2) identifying the first job site location based on the location information of the telematic data, (3) retrieving location information for existing job sites from a job site database, and (4) determining that the first job site location is not within one of the existing job sites, wherein the one or more tools comprises a handheld tool, wherein determining that the one or more tools have been used comprises: detecting, from the telematic data, that the handheld tool has lost a wireless connection to the equipment; based on detecting that the handheld tool has lost the wireless connection to the equipment, determining that the handheld tool has left the equipment; and based on detecting that the handheld tool has left the equipment, determining that the handheld tool is in use; in response to determining that the first job site location is a new job site, updating the job site database to include the first job site location; generating aggregated data based on the telematic data and an equipment record associated with the piece of equipment; and presenting the aggregated data on a user computing device through a portal comprising a graphical user interface, wherein the portal is configured to allow a user to generate a report associated with the piece of equipment, wherein the report includes information related to time spent by the piece of equipment at one or more job site locations in the job site database, the one or more job site locations including the first job site location. 